1. Field of the Invention
The present invention concerns a method to correct image distortions that can occur in the acquisition of diffusion-weighted magnetic resonance images (also called “MR images” in the following) of an examination subject, as well as a magnetic resonance system (also called an “MR system” in the following) with which such a method can be implemented.
2. Description of the Prior Art
In diffusion imaging, multiple images are normally acquired with different diffusion directions and diffusion weightings and combined with one another. The strength of the diffusion weighting is primarily defined by a factor known as the “b-value”. The diffusion images with different diffusion directions and diffusion weightings, or images combined from such images can then be used for diagnostic purposes. Parameter maps with particular diagnostic significance thus can be generated by suitable combinations of the acquired diffusion-weighted images, for example maps that reflect the “Apparent Diffusion Coefficient (ADC)” or the “Fractional Anisotropy (FA)”.
Eddy current fields can be caused by the diffusion gradients, and such eddy current fields in turn lead to image distortions whose appearance depends both on the amplitude of the gradients—i.e. the diffusion weighting—and on their direction. If the acquired individual images are then combined with one another without correction, for example in order to generate the cited parameter maps, the different distortions for each image lead to incorrect associations of pixel information, and therefore to errors or at least to a reduced precision of the calculated parameters. Particularly, in diffusion-weighted images that were acquired with the use of the echoplanar technique (EPI), eddy current-dependent distortions represent a particularly significant challenge since there is typically a particularly high sensitivity (approximately 10 Hz per pixel in the phase coding direction) to static and dynamic field disruptions in EPI imaging, and is precisely in that context that high gradient amplitudes are used to adjust the diffusion gradients.
The complex spatial geometry of the original dynamic interference fields leads to the situation that, in multislice exposures, the distortions depend on the position and orientation of every individual slice.
Multiple image-based methods are known for the correction of eddy current-dependent distortions in diffusion imaging. For example, in a publication by Haselgrove et al. (in MRM 36: 960-964, 1996) a method is described in which initially an undistorted MR reference image is acquired with a diffusion weighting b=0, i.e. without application of a diffusion gradient. Furthermore, a second adjustment measurement with low diffusion weighting for the direction to be corrected is acquired. A low diffusion weighting thereby means a b-value of 150 s/m2, for example. It is then assumed that the distortions in the images can be described in good approximation as simple affine transformations with a scaling N, a shear S and a shift or a translation T. Therefore distortion parameters for M, S and T are determined with the use of the two adjustment measurements, i.e. the measurement of the reference image and the image with low diffusion weighting. The distortion parameters M, S and T that are thus determined are then used (using an extrapolation relationship) for the correction of the actual diffusion-weighted usable MR images, in which the b-value amounts to 1000 s/m2, for example. This method requires at least one adjustment measurement for each diffusion direction.
Furthermore, in a publication by Bodammer et al. (in MRM 51: 188-193, 2004) a method is described in which two images with identical diffusion direction and diffusion weighting but inverted polarity are acquired within the scope of adjustment measurements. While the diffusion contrast remains unchanged given an inverted polarity, the inversion affects the distortion as an inversion. This means that an elongation becomes a compression, a positive shear becomes a negative shear and a positive translation becomes a negative translation. In this method two images must respectively be acquired for each diffusion direction and for each diffusion weighting.
It is common to the methods that they each operate at individual slices, meaning that a registration of the distorted image with a reference image is conducted individually for each slice. Two classes of methods can thereby be differentiated:
A) The direct registration of the measurement data:
A reference image is hereby acquired for each slice during the measurement, normally at the beginning of the measurement. All distorted images acquired during the measurement are then immediately deskewed via a registration to the corresponding reference image. This procedure has the advantage that the correction is independent of model assumptions. However, the process time—i.e. the calculation time for deskewing—is relatively long.
B) Use of an adjustment measurement:
Targeted reference images and defined distorted images are hereby acquired before the actual measurement—for example via application of only one x-, y- or z-diffusion gradient with a specific amplitude—and the deskewing parameters are calculated for the defined distorted images. From these values, suitable correction parameters for the images of the usable measurements are calculated on the basis of physical model assumptions. In general it is assumed that the distortions of the three gradient axes overlap in an undistorted manner, and that the distortions scale linearly with the gradient amplitude. This method has the advantage that it also functions for measurement data with a very low SNR (signal-to-noise ratio), for example given very high b-values during the actual usable measurement, since the adjustment measurement can be implemented with smaller b-values. Given a suitable embodiment of the method, this is robust against movement influences. Such a method is described in DE 10 2009 003 883 B3, for example. However, in this method the measurement time is relatively long due to the additional adjustment measurements.